Stella Modulates Transcriptional and Endogenous Retrovirus Programs
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Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Crystal Structure of LSD1 in Complex with 4-[5-(Piperidin-4-Ylmethoxy)-2-(P-Tolyl) Pyridin-3-Yl]Benzonitrile
molecules Article Crystal Structure of LSD1 in Complex with 4-[5-(Piperidin-4-ylmethoxy)-2-(p-tolyl) pyridin-3-yl]benzonitrile Hideaki Niwa 1 ID , Shin Sato 1, Tomoko Hashimoto 2, Kenji Matsuno 2 and Takashi Umehara 1,* ID 1 Laboratory for Epigenetics Drug Discovery, RIKEN Center for Biosystems Dynamics Research (BDR), 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan; [email protected] (H.N.); [email protected] (S.S.) 2 Department of Chemistry and Life Science, School of Advanced Engineering, Kogakuin University, 2665-1 Nakano, Hachioji, Tokyo 192-0015, Japan; [email protected] (T.H.); [email protected] (K.M.) * Correspondence: [email protected]; Tel.: +81-45-503-9457 Received: 28 May 2018; Accepted: 22 June 2018; Published: 26 June 2018 Abstract: Because lysine-specific demethylase 1 (LSD1) regulates the maintenance of cancer stem cell properties, small-molecule inhibitors of LSD1 are expected to be useful for the treatment of several cancers. Reversible inhibitors of LSD1 with submicromolar inhibitory potency have recently been reported, but their exact binding modes are poorly understood. In this study, we synthesized a recently reported reversible inhibitor, 4-[5-(piperidin-4-ylmethoxy)-2-(p-tolyl)pyridin-3- yl]benzonitrile, which bears a 4-piperidinylmethoxy group, a 4-methylphenyl group, and a 4-cyanophenyl group on a pyridine ring, and determined the crystal structure of LSD1 in complex with this inhibitor at 2.96 Å. We observed strong electron density for the compound, showing that its cyano group forms a hydrogen bond with Lys661, which is a critical residue in the lysine demethylation reaction located deep in the catalytic center of LSD1. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
82594016.Pdf
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Structure Article Molecular Mimicry and Ligand Recognition in Binding and Catalysis by the Histone Demethylase LSD1-CoREST Complex Riccardo Baron,1,* Claudia Binda,2 Marcello Tortorici,2 J. Andrew McCammon,1 and Andrea Mattevi2,* 1Department of Chemistry and Biochemistry, Center for Theoretical Biological Physics, and Department of Pharmacology, Howard Hughes Medical Institute, University of California at San Diego, La Jolla, CA 92093-0365, USA 2Department of Genetics and Microbiology, University of Pavia, Via Ferrata 1, 27100, Pavia, Italy *Correspondence: [email protected] (R.B.), [email protected] (A.M.) DOI 10.1016/j.str.2011.01.001 SUMMARY (LSD1 or KDM1A, according to the newly adopted nomencla- ture) (Shi et al., 2004; Forneris et al., 2005). This enzyme acts Histone demethylases LSD1 and LSD2 (KDM1A/B) on mono- and dimethylated Lys4 of histone H3 through a catalyze the oxidative demethylation of Lys4 of FAD-dependent oxidative process (Figure 1A). LSD1 is often histone H3. We used molecular dynamics simula- associated to the histone deacetylases (HDAC) 1 and 2 and to tions to probe the diffusion of the oxygen substrate. the corepressor protein CoREST, which tightly binds to LSD1 Oxygen can reach the catalytic center independently enhancing both its stability and enzymatic activity. A number of from the presence of a bound histone peptide, studies have indicated that LSD1-CoREST interacts with various protein complexes involved in gene regulation and chromatin implying that LSD1 can complete subsequent deme- modification (Forneris et al., 2008; Mosammaparast and Shi, thylation cycles without detaching from the nucleo- 2010). -
Partial Deletion of Chromosome 6P Causing Developmental Delay and Mild Dysmorphisms in a Child
Vrachnis et al. Mol Cytogenet (2021) 14:39 https://doi.org/10.1186/s13039-021-00557-y CASE REPORT Open Access Partial deletion of chromosome 6p causing developmental delay and mild dysmorphisms in a child: molecular and developmental investigation and literature search Nikolaos Vrachnis1,2,3* , Ioannis Papoulidis4, Dionysios Vrachnis5, Elisavet Siomou4, Nikolaos Antonakopoulos1,2, Stavroula Oikonomou6, Dimitrios Zygouris2, Nikolaos Loukas7, Zoi Iliodromiti8, Efterpi Pavlidou9, Loretta Thomaidis6 and Emmanouil Manolakos4 Abstract Background: The interstitial 6p22.3 deletions concern rare chromosomal events afecting numerous aspects of both physical and mental development. The syndrome is characterized by partial deletion of chromosome 6, which may arise in a number of ways. Case presentation: We report a 2.8-year old boy presenting with developmental delay and mild dysmorphisms. High-resolution oligonucleotide microarray analysis revealed with high precision a 2.5 Mb interstitial 6p deletion in the 6p22.3 region which encompasses 13 genes. Conclusions: Identifcation and in-depth analysis of cases presenting with mild features of the syndrome will sharpen our understanding of the genetic spectrum of the 6p22.3 deletion. Keywords: 6p22.3 deletion, Syndrome, Developmental delay, Intellectual disability, Dysmorphism, Behavioral abnormalities, High-resolution microarray analysis Background dysmorphic features, and structural organ defects, as well Te interstitial deletion of chromosomal region 6p22.3 as intellectual disability. is a rare condition with variable phenotypic expression. We report herein a case of interstitial deletion of chro- To date, more than 30 children and adolescents with this mosome 6p investigated by array-CGH in a 2.8-year old deletion have been reported [1–11]. -
Multivariate Meta-Analysis of Differential Principal Components Underlying Human Primed and Naive-Like Pluripotent States
bioRxiv preprint doi: https://doi.org/10.1101/2020.10.20.347666; this version posted October 21, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license. October 20, 2020 To: bioRxiv Multivariate Meta-Analysis of Differential Principal Components underlying Human Primed and Naive-like Pluripotent States Kory R. Johnson1*, Barbara S. Mallon2, Yang C. Fann1, and Kevin G. Chen2*, 1Intramural IT and Bioinformatics Program, 2NIH Stem Cell Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892, USA Keywords: human pluripotent stem cells; naive pluripotency, meta-analysis, principal component analysis, t-SNE, consensus clustering *Correspondence to: Dr. Kory R. Johnson ([email protected]) Dr. Kevin G. Chen ([email protected]) 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.10.20.347666; this version posted October 21, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license. ABSTRACT The ground or naive pluripotent state of human pluripotent stem cells (hPSCs), which was initially established in mouse embryonic stem cells (mESCs), is an emerging and tentative concept. To verify this important concept in hPSCs, we performed a multivariate meta-analysis of major hPSC datasets via the combined analytic powers of percentile normalization, principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and SC3 consensus clustering. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Pathogenic Variants in the DEAH-Box RNA Helicase DHX37 Are a Frequent Cause of 46,XY Gonadal Dysgenesis and 46,XY Testicular Regression Syndrome
ARTICLE © American College of Medical Genetics and Genomics Pathogenic variants in the DEAH-box RNA helicase DHX37 are a frequent cause of 46,XY gonadal dysgenesis and 46,XY testicular regression syndrome Ken McElreavey, PhD 1, Anne Jorgensen, PhD 2, Caroline Eozenou, PhD1, Tiphanie Merel, MSc1, Joelle Bignon-Topalovic, BSc1, Daisylyn Senna Tan, BSc3, Denis Houzelstein, PhD 1, Federica Buonocore, PhD 4, Nick Warr, PhD 5, Raissa G. G. Kay, PhD5, Matthieu Peycelon, MD, PhD 6,7,8, Jean-Pierre Siffroi, MD, PhD6, Inas Mazen, MD9, John C. Achermann, MD, PhD 4, Yuliya Shcherbak, MD10, Juliane Leger, MD, PhD11, Agnes Sallai, MD 12, Jean-Claude Carel, MD, PhD 11, Laetitia Martinerie, MD, PhD11, Romain Le Ru, MD13, Gerard S. Conway, MD, PhD14, Brigitte Mignot, MD15, Lionel Van Maldergem, MD, PhD 16, Rita Bertalan, MD, PhD17, Evgenia Globa, MD, PhD 18, Raja Brauner, MD, PhD19, Ralf Jauch, PhD 3, Serge Nef, PhD 20, Andy Greenfield, PhD5 and Anu Bashamboo, PhD1 Purpose: XY individuals with disorders/differences of sex devel- specifically associated with gonadal dysgenesis and TRS. opment (DSD) are characterized by reduced androgenization Consistent with a role in early testis development, DHX37 is caused, in some children, by gonadal dysgenesis or testis regression expressed specifically in somatic cells of the developing human during fetal development. The genetic etiology for most patients and mouse testis. with 46,XY gonadal dysgenesis and for all patients with testicular Conclusion: DHX37 pathogenic variants are a new cause of an regression syndrome (TRS) is unknown. autosomal dominant form of 46,XY DSD, including gonadal Methods: We performed exome and/or Sanger sequencing in 145 dysgenesis and TRS, showing that these conditions are part of a individuals with 46,XY DSD of unknown etiology including clinical spectrum. -
Official Symbol Accession Alias / Previous Symbol Official Full Name
Official Symbol Accession Alias / Previous Symbol Official Full Name Abcc3 NM_029600.3 1700019L09Rik,MRP3,RIKEN cDNA 1700019L09 gene ATP-binding cassette, sub-family C (CFTR/MRP), member 3 Abcc8 NM_011510.3 D930031B21Rik,MGD-MRK-33673,MGI:105993,MGI:3036285,RIKEN cDNA D930031B21ATP-binding gene,sulfonylurea cassette, sub-familyreceptor,Sur,SUR1 C (CFTR/MRP), member 8 Abl1 NM_009594.4 AI325092,c-Abl,E430008G22Rik,expressed sequence AI325092,MGD-MRK-1015,MGI:2138905,MGI:2443781,RIKENc-abl oncogene 1, non-receptor cDNAtyrosine E430008G22 kinase gene Adamts16 NM_172053.2 MGC:37086 a disintegrin-like and metallopeptidase (reprolysin type) with thrombospondin type 1 motif, 16 Ago4 NM_153177.3 5730550L01Rik,AI481660,argonaute 4,Eif2c4,eukaryotic translation initiation factorargonaute 2C, 4,expressed RISC catalytic sequence subunit AI481660,MGI:2140312,RIKEN 4 cDNA 5730550L01 gene Agt NM_007428.3 AI265500,angiotensin precursor,Aogen,expressed sequence AI265500,MGD-MRK-1192,MGI:2142488,Serpina8angiotensinogen (serpin peptidase inhibitor, clade A, member 8) AI464131 NM_001085515.2 AA408153,AI604836,expressed sequence AA408153,expressed sequence expressedexpressed sequence sequence AI604836,gene AI464131 model 762, (NCBI),Gm762,MGI:2140126,MGI:2140342,MGI:2685608,NET37 Ak1 NM_001198790.1 Ak-1,B430205N08Rik,MGD-MRK-1240,MGD-MRK-1244,MGI:2445070,RIKEN cDNA B430205N08adenylate kinase gene 1 Akt1 NM_001165894.1 Akt,MGD-MRK-1257,PKB,PKB/Akt,PKBalpha thymoma viral proto-oncogene 1 Akt2 NM_001110208.1 2410016A19Rik,AW554154,expressed sequence AW554154,MGD-MRK-28173,MGI:1923730,MGI:2142261,PKB,PKBbeta,RIKENthymoma -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Mouse Dppa3 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Dppa3 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Dppa3 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Dppa3 gene (NCBI Reference Sequence: NM_139218 ; Ensembl: ENSMUSG00000046323 ) is located on Mouse chromosome 6. 4 exons are identified, with the ATG start codon in exon 1 and the TAG stop codon in exon 4 (Transcript: ENSMUST00000049644). Exon 2 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Dppa3 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP24-68I7 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Female mice homozygous for a disruption in this gene are infertile or have reduced fertility due to a failure in embryonic development at or before implantation. Exon 2 starts from about 19.78% of the coding region. The knockout of Exon 2 will result in frameshift of the gene. The size of intron 1 for 5'-loxP site insertion: 1966 bp, and the size of intron 2 for 3'-loxP site insertion: 491 bp. The size of effective cKO region: ~728 bp. The cKO region does not have any other known gene. Page 1 of 7 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 2 3 4 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Homology arm Exon of mouse Dppa3 cKO region loxP site Page 2 of 7 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
Inferring Biological Networks from Genome-Wide Transcriptional And
INFERRING BIOLOGICAL NETWORKS FROM GENOME-WIDE TRANSCRIPTIONAL AND FITNESS DATA By WAZEER MOHAMMAD VARSALLY A thesis submitted to The University of Birmingham for the degree of Doctor of Philosophy College of Life and Environmental Sciences School of Biosciences The University of Birmingham July 2013 I University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT In the last 15 years, the increased use of high throughput biology techniques such as genome-wide gene expression profiling, fitness profiling and protein interactomics has led to the generation of an extraordinary amount of data. The abundance of such diverse data has proven to be an essential foundation for understanding the complexities of molecular mechanisms and underlying pathways within a biological system. One approach of extrapolating biological information from this wealth of data has been through the use of reverse engineering methods to infer biological networks. This thesis demonstrates the capabilities and applications of such methodologies in identifying functionally enriched network modules in the yeast species Saccharomyces cerevisiae and Schizosaccharomyces pombe. This study marks the first time a mutual information based network inference approach has been applied to a set of specific genome-wide expression and fitness compendia, as well as the integration of these multi- level compendia.